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Thomas Blumensath
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2020 – today
- 2023
- [i12]Zhenduo Shang, Thomas Blumensath:
Stereo X-ray Tomography. CoRR abs/2302.13207 (2023) - [i11]Raziye Kubra Kumrular, Thomas Blumensath:
Invertible Low-Dimensional Modelling of X-ray Absorption Spectra for Potential Applications in Spectral X-ray Imaging. CoRR abs/2307.04484 (2023) - 2022
- [c17]Andrea Napoli, Paul R. White, Thomas Blumensath:
Quantity Over Quality? Investigating the Effects of Volume and Strength of Training Data in Marine Bioacoustics. DCASE 2022 - [i10]Emilien Valat, Katayoun Farrahi
, Thomas Blumensath
:
Sinogram Enhancement with Generative Adversarial Networks using Shape Priors. CoRR abs/2202.00419 (2022) - [i9]Emilien Valat, Katayoun Farrahi
, Thomas Blumensath
:
Data-Driven Interpolation for Super-Scarce X-Ray Computed Tomography. CoRR abs/2205.07888 (2022) - 2021
- [c16]Peng Chen
, Mohamed Wahib, Xiao Wang
, Takahiro Hirofuchi, Hirotaka Ogawa, Ander Biguri, Richard P. Boardman, Thomas Blumensath, Satoshi Matsuoka:
Scalable FBP decomposition for cone-beam CT reconstruction. SC 2021: 9 - 2020
- [j17]Ander Biguri
, Reuben Lindroos, Robert Bryll
, Hossein Towsyfyan, Hans Deyhle
, Ibrahim El Khalil Harrane, Richard P. Boardman
, Mark Mavrogordato, Manjit Dosanjh
, Steven Hancock, Thomas Blumensath
:
Arbitrarily large tomography with iterative algorithms on multiple GPUs using the TIGRE toolbox. J. Parallel Distributed Comput. 146: 52-63 (2020)
2010 – 2019
- 2019
- [i8]Yushan Gao, Ander Biguri
, Thomas Blumensath:
Block stochastic gradient descent for large-scale tomographic reconstruction in a parallel network. CoRR abs/1903.11874 (2019) - [i7]Ander Biguri
, Reuben Lindroos, Robert Bryll, Hossein Towsyfyan, Hans Deyhle, Richard P. Boardman, Mark Mavrogordato, Manjit Dosanjh, Steven Hancock, Thomas Blumensath:
Arbitrarily large iterative tomographic reconstruction on multiple GPUs using the TIGRE toolbox. CoRR abs/1905.03748 (2019) - [i6]Ander Biguri, Hossein Towsyfyan, Richard P. Boardman, Thomas Blumensath:
Numerically robust tetrahedron-based tomographic forward and backward projectors on parallel architectures. CoRR abs/1908.06909 (2019) - 2018
- [j16]Thomas Blumensath
:
Backprojection inverse filtration for laminographic reconstruction. IET Image Process. 12(9): 1531-1539 (2018) - [j15]Yushan Gao
, Thomas Blumensath
:
A Joint Row and Column Action Method for Cone-Beam Computed Tomography. IEEE Trans. Computational Imaging 4(4): 599-608 (2018) - [i5]Yushan Gao, Thomas Blumensath:
BSGD-TV: A parallel algorithm solving total variation constrained image reconstruction problems. CoRR abs/1812.01307 (2018) - 2017
- [i4]Yushan Gao, Thomas Blumensath:
Distributed Computation of Linear Inverse Problems with Application to Computed Tomography. CoRR abs/1709.00953 (2017) - 2016
- [j14]Thomas Blumensath
:
Directional Clustering Through Matrix Factorization. IEEE Trans. Neural Networks Learn. Syst. 27(10): 2095-2107 (2016) - 2014
- [c15]Alexis Benichoux, Thomas Blumensath:
A spatially constrained low-rank matrix factorization for the functional parcellation of the brain. EUSIPCO 2014: 26-30 - [c14]Thomas Blumensath:
Sparse matrix decompositions for clustering. EUSIPCO 2014: 1163-1167 - [c13]Thomas Blumensath
:
Monte Carlo methods for compressed sensing. ICASSP 2014: 1000-1004 - 2013
- [j13]Thomas Blumensath
, Saâd Jbabdi, Matthew F. Glasser, David C. Van Essen, Kâmil Ugurbil, Timothy Edward John Behrens
, Stephen M. Smith
:
Spatially constrained hierarchical parcellation of the brain with resting-state fMRI. NeuroImage 76: 313-324 (2013) - [j12]Thomas Blumensath
:
Compressed Sensing With Nonlinear Observations and Related Nonlinear Optimization Problems. IEEE Trans. Inf. Theory 59(6): 3466-3474 (2013) - 2012
- [j11]Thomas Blumensath
:
Accelerated iterative hard thresholding. Signal Process. 92(3): 752-756 (2012) - [c12]Thomas Blumensath, Timothy Edward John Behrens
, Stephen M. Smith
:
Resting-State FMRI Single Subject Cortical Parcellation Based on Region Growing. MICCAI (2) 2012: 188-195 - [p1]Thomas Blumensath
, Michael E. Davies, Gabriel Rilling:
Greedy algorithms for compressed sensing. Compressed Sensing 2012: 348-393 - [i3]Thomas Blumensath:
Compressed Sensing with Nonlinear Observations and Related Nonlinear Optimisation Problems. CoRR abs/1205.1650 (2012) - 2011
- [j10]Thomas Blumensath
:
Sampling and Reconstructing Signals From a Union of Linear Subspaces. IEEE Trans. Inf. Theory 57(7): 4660-4671 (2011) - 2010
- [j9]Thomas Blumensath
, Michael E. Davies:
Normalized Iterative Hard Thresholding: Guaranteed Stability and Performance. IEEE J. Sel. Top. Signal Process. 4(2): 298-309 (2010) - [j8]Mark D. Plumbley
, Thomas Blumensath
, Laurent Daudet, Rémi Gribonval, Mike E. Davies:
Sparse Representations in Audio and Music: From Coding to Source Separation. Proc. IEEE 98(6): 995-1005 (2010)
2000 – 2009
- 2009
- [j7]Thomas Blumensath
, Michael E. Davies:
Sampling Theorems for Signals From the Union of Finite-Dimensional Linear Subspaces. IEEE Trans. Inf. Theory 55(4): 1872-1882 (2009) - [j6]Mehrdad Yaghoobi, Thomas Blumensath
, Mike E. Davies:
Dictionary learning for sparse approximations with the majorization method. IEEE Trans. Signal Process. 57(6): 2178-2191 (2009) - [j5]Thomas Blumensath
, Mike E. Davies:
Stagewise weak gradient pursuits. IEEE Trans. Signal Process. 57(11): 4333-4346 (2009) - [c11]Mehrdad Yaghoobi, Thomas Blumensath
, Michael E. Davies:
Parsimonious dictionary learning. ICASSP 2009: 2869-2872 - [c10]Thomas Blumensath
, Mike E. Davies:
A simple, efficient and near optimal algorithm for compressed sensing. ICASSP 2009: 3357-3360 - [i2]Thomas Blumensath:
Sampling and reconstructing signals from a union of linear subspaces. CoRR abs/0911.3514 (2009) - 2008
- [j4]Thomas Blumensath
, Michael E. Davies:
Gradient Pursuits. IEEE Trans. Signal Process. 56(6): 2370-2382 (2008) - [c9]Thomas Blumensath, Mike E. Davies:
Gradient pursuit for non-linear sparse signal modelling. EUSIPCO 2008: 1-5 - [c8]Mehrdad Yaghoobi, Thomas Blumensath, Mike E. Davies:
Regularized dictionary learning for sparse approximation. EUSIPCO 2008: 1-5 - [i1]Thomas Blumensath, Mike E. Davies:
Iterative Hard Thresholding for Compressed Sensing. CoRR abs/0805.0510 (2008) - 2007
- [j3]Thomas Blumensath
, Michael E. Davies:
Monte Carlo Methods for Adaptive Sparse Approximations of Time-Series. IEEE Trans. Signal Process. 55(9): 4474-4486 (2007) - [c7]Thomas Blumensath, Mike E. Davies:
In greedy PURSUIT of new directions: (Nearly) Orthogonal Matching Pursuit by directional optimisation. EUSIPCO 2007: 340-344 - [c6]Thomas Blumensath, Mike E. Davies:
Compressed Sensing and Source Separation. ICA 2007: 341-348 - [c5]Mehrdad Yaghoobi, Thomas Blumensath
, Mike E. Davies:
Quantized Sparse Approximation with Iterative Thresholding for Audio Coding. ICASSP (1) 2007: 257-260 - [c4]Thomas Blumensath
, Mehrdad Yaghoobi, Mike E. Davies:
Iterative Hard Thresholding and L0 Regularisation. ICASSP (3) 2007: 877-880 - 2006
- [j2]Mark D. Plumbley
, Samer A. Abdallah, Thomas Blumensath
, Michael E. Davies:
Sparse representations of polyphonic music. Signal Process. 86(3): 417-431 (2006) - [j1]Thomas Blumensath
, Mike E. Davies:
Sparse and shift-Invariant representations of music. IEEE Trans. Speech Audio Process. 14(1): 50-57 (2006) - 2005
- [c3]Thomas Blumensath
, Mike E. Davies:
A fast importance sampling algorithm for unsupervised learning of over-complete dictionaries. ICASSP (5) 2005: 213-216 - 2004
- [c2]Thomas Blumensath, Mike E. Davies:
On Shift-Invariant Sparse Coding. ICA 2004: 1205-1212 - [c1]Thomas Blumensath, Mike E. Davies:
Unsupervised learning of sparse and shift-invariant decompositions of polyphonic music. ICASSP (5) 2004: 497-500
Coauthor Index
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